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Intelligent healthcare forms analysis with Amazon Bedrock

AWS Machine Learning

Amazon Bedrock is a fully managed service that makes foundation models (FMs) from leading AI startups and Amazon available through an API, so you can choose from a wide range of FMs to find the model that is best suited for your use case. Whenever a new form is loaded, an event is invoked in Amazon SQS.

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Using LLMs to fortify cyber defenses: Sophos’s insight on strategies for using LLMs with Amazon Bedrock and Amazon SageMaker

AWS Machine Learning

SOC analysts continuously monitor security events, investigate potential threats, and take appropriate action to mitigate risks. Security incidents typically consist of a series of events occurring on a user endpoint or network, associated with detected suspicious activity. As a cybersecurity assistant, your task is to: 1.

APIs 99
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Generate and evaluate images in Amazon Bedrock with Amazon Titan Image Generator G1 v2 and Anthropic Claude 3.5 Sonnet

AWS Machine Learning

Sonnet, also newly released, setting new industry benchmarks for graduate-level reasoning and improvements in grasping complex instructions. It exposes an API endpoint through Amazon API Gateway that proxies the initial prompt request to a Python-based AWS Lambda function, which calls Amazon Bedrock twice. Choose Next again.

APIs 105
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Optimize your machine learning deployments with auto scaling on Amazon SageMaker

AWS Machine Learning

Although you can integrate the model directly into an application, the approach that works well for production-grade applications is to deploy the model behind an endpoint and then invoke the endpoint via a RESTful API call to obtain the inference. However, you can use any other benchmarking tool. large two-core machine.

Benchmark 100
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Accelerate disaster response with computer vision for satellite imagery using Amazon SageMaker and Amazon Augmented AI

AWS Machine Learning

Two key distinctions are the low altitude, oblique perspective of the imagery and disaster-related features, which are rarely featured in computer vision benchmarks and datasets. These LADI datasets focus on the Atlantic hurricane seasons and coastal states along the Atlantic Ocean and Gulf of Mexico.

APIs 100
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A review of purpose-built accelerators for financial services

AWS Machine Learning

In terms of resulting speedups, the approximate order is programming hardware, then programming against PBA APIs, then programming in an unmanaged language such as C++, then a managed language such as Python. The CUDA API and SDK were first released by NVIDIA in 2007. GPU PBAs, 4% other PBAs, 4% FPGA, and 0.5%

Benchmark 104
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How to Successfully Implement Customer Journey Analytics – Part 1

Pointillist

Thinking in Events. The fundamental data type for customer journey analytics is the event. Regardless of how you might think of data today, in customer journey analytics everything is an event. Treating every change to customer data as an event saves work for data engineers, as no transformation is required.